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Bayesian sequential data assimilation for COVID-19 forecasting
We introduce a Bayesian sequential data assimilation and forecasting method for non-autonomous dynamical systems. We applied this method to the current COVID-19 pandemic. It is assumed that suitable transmission, epidemic and observation models are available and previously validated. The transmissio...
Autores principales: | Daza-Torres, Maria L., Capistrán, Marcos A., Capella, Antonio, Christen, J. Andrés |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9023479/ https://www.ncbi.nlm.nih.gov/pubmed/35487155 http://dx.doi.org/10.1016/j.epidem.2022.100564 |
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